Per-agent spend-cap and anomaly-block runtime for cloud API keys and LLM integrations
A runtime that sits between agents and third-party APIs (OpenAI, Google Cloud, Anthropic, AWS) and enforces programmable per-agent spend caps, anomaly detection, and instant kill-switches without requiring manual monitoring or post-facto billing forensics.
The problem
Developers deploying autonomous agents risk catastrophic runaway API charges when keys are compromised or agents enter infinite loops; a single leaked key or agent malfunction can bill $82k in 48 hours against a $180/month baseline, forcing shutdown and financial ruin with no real-time defense or granular control per agent.
Who has it: Series A/B AI-native startups and mid-market enterprises deploying autonomous agents calling OpenAI, Google Cloud, or Anthropic APIs with >$5k/month cloud spend and no existing per-agent spend governance.
Why now: Autonomous agents are moving into production at enterprises and startups; traditional API key management (vault, rotation, audit logs) does not prevent runaway consumption; LLM usage is volatile and agents introduce non-deterministic loops that can drain budgets faster than humans can respond.
Where this came from
2 public sources behind this idea.
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